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Modelling of soot formation in a heavy-duty diesel engine with conditional moment closure

机译：有条件力矩封闭的重型柴油机中烟灰形成的模型

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摘要

This study presents the first application of a multidimensional conditional moment closure (CMC) combustion with a two-equation soot model to study the evolution of in-cylinder soot in diesel engines. Five high-fidelity reference cases from an optically accessible heavy-duty diesel engine were used to validate the model predictions; these include two high-temperature cases and two low-temperature cases with two different injection timings and one low-temperature case with a split injection strategy. Simulation results have been compared with experimental data by means of non-reactive fuel vapour distribution, apparent heat release rates (AHRR), temporal evolutions of quantitative in-cylinder soot mass and natural luminosity. The model was capable to reproduce semi-quantitative trends of soot mass for all five cases. In particular for low-temperature conditions the evolution of soot formation and oxidation is very well captured. A line-of-sight transformation of the computed 3D soot is proposed to ensure a consistent comparison with the measured 2D soot natural luminosity images. With this methodology additional effects related to radiation adsorption were observed. Evolutions of line-of-sight soot natural luminosity were qualitatively very well reproduced. Overall the findings suggest that the presented two-equation soot model implemented in the CMC framework is a highly promising candidate for predicting time evolutions of in-cylinder soot for diesel engines operating in different combustion modes.
机译：这项研究提出了带有两个方程式烟灰模型的多维条件矩闭合（CMC）燃烧的首次应用，以研究柴油机缸内烟灰的演变。来自光学可访问的重型柴油机的五个高保真参考案例用于验证模型预测。其中包括两个高温情况和两个具有两个不同喷射定时的低温情况，以及一个具有分段喷射策略的低温情况。通过非反应性燃料蒸气分布，表观放热率（AHRR），定量缸内烟灰质量随时间变化和自然发光度，将模拟结果与实验数据进行了比较。该模型能够再现所有五种情况下烟尘质量的半定量趋势。特别是在低温条件下，炭黑形成和氧化的演变得到了很好的捕获。建议对计算的3D烟灰进行视线转换，以确保与测量的2D烟灰自然光度图像保持一致。通过这种方法，观察到了与辐射吸收有关的其他影响。定性地很好地再现了视线煤烟自然光度的演变。总体而言，这些发现表明，在CMC框架中实施的提出的两方程式烟灰模型是预测在不同燃烧模式下运行的柴油机缸内烟灰时间演变的极有希望的候选者。

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